A Strategic Rail Network Optimization Model for Freight Transportation

An optimization model for a rail freight network was developed as asupport tool for planning and policy decisions involved in the improvementof rail networks on a regional and national level. The model wasbased on a strategic traffic assignment model, which was designed tomodel macronetworks with a...

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Bibliographic Details
Main Author: Luís Couto Maia (author)
Other Authors: António Fidalgo Couto (author)
Format: book
Language:eng
Published: 2013
Subjects:
Online Access:https://repositorio-aberto.up.pt/handle/10216/93949
Country:Portugal
Oai:oai:repositorio-aberto.up.pt:10216/93949
Description
Summary:An optimization model for a rail freight network was developed as asupport tool for planning and policy decisions involved in the improvementof rail networks on a regional and national level. The model wasbased on a strategic traffic assignment model, which was designed tomodel macronetworks with a high aggregation level, and was exclusivelydesigned for freight traffic. The model contemplates road and railtransport modes and considers two types of cargo: intermodal cargo,which is generally transported in containers and is easily interchangedbetween different modes at intermodal terminals, and general cargo,which represents all the remaining cargo. The optimization process wasbased on a local search heuristic that delivers good solutions in a reasonablecomputing time. The quality of each network improvement solutionwas assessed on the basis of the reductions in total generalized costsand carbon dioxide emissions. This optimization model for a freightnetwork is innovative because it is not limited: both the improvementof existing links and the construction of new ones are allowed, and themodel does not have a limit on the number or variety of possibilitiesfor network improvement. The adaptability to different conditions wasemphasized when the model was applied to two networks under differentinvestment scenarios because the model delivered considerablydifferent solutions adapted to the conditions of each scenario.